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The Autonomous Systems National Laboratory (ARNL) held its annual research and development demonstration day entitled "Innovation in Motion" at the ZalaZONE Industrial Park in Zalaegerszeg, Hungary on 26 May 2025. The event featured presentations of the latest developments by the HUN-REN Institute for Computer Science and Control, the Budapest University of Technology and Economics, and Széchenyi István University, all members of the ARNL consortium. The demonstration day highlighted that domestic research into autonomous systems is based on strong foundations, both from a scientific and practical perspective, and offers real answers to the transport and industrial challenges of the future.

With the advent of autonomous vehicles, a future where human drivers are no longer needed and only "self-driving" cars are on the road has emerged. But can this happen, why do we need autonomous cars at all, and how could connected autonomous vehicles improve transport efficiency? The head of Systems and Control Laboratory (SCL) at HUN-REN SZTAKI now explains how we should imagine it all.

When we hear of delivery drones, many people imagine a future scenario: hovering devices delivering orders directly to the balcony or front gate. But the reality is much more complex than that, and the biggest challenge is to ensure that these devices can navigate autonomously, safely and reliably in an often unpredictable urban environment. In this area, experts at the Systems and Control Laboratory (SCL) at HUN-REN SZTAKI have achieved world-class results by developing intelligent control solutions that enable drones to react to changes in the environment in real time – all with minimal energy consumption.

Every year, millions of road accidents occur worldwide and the vast majority of them – around 94% – are caused by human error. What if vehicles could anticipate risks and react faster than even the best drivers? HUN-REN SZTAKI SCL is working on this in collaboration with the world's leading technology and engineering companies.

Members of HUN-REN SZTAKI Systems and Control Research Lab, Balázs Németh, lead researcher of ARNL, as well as Csanád Budai and Tamás Széles, researchers of ARNL, gave lectures on the topic of “Artificial Intelligence and Autonomous Vehicles” at the Reformed High School of Pécs on 16 April 2025.

This year, for the seventh time, the BME Faculty of Transportation Engineering and Vehicle Engineering (BME KJK) organised the event, which offered an exciting programme for those interested in transport, automotive, logistics and aeronautics.

BME's lecturers and researchers gave a brief overview of the specialisation in vehicle mechatronics and career opportunities. In addition to the model vehicles of the BME Faculty of Transportation Engineering and Vehicle Engineering (BME KJK), the autonomous experimental vehicle platform of ARNL was presented.

Bálint Vanek, senior researcher at HUN-REN SZTAKI’s Systems and Control Lab and lead researcher of ARNL, delivered a Flutter Control Workshop at Airbus UpNext, the advanced research and innovation division of Airbus, in Toulouse, France. The workshop focused on key insights from the successful flight demonstrations of active flutter suppression carried out in the framework of the FLEXOP and FliPASED H2020 projects and the methodologies that supported these outcomes. The presentation also underlined the projects’ influence on flight safety and their recognition by EASA experts.

Bálint Vanek, senior researcher at HUN-REN SZTAKI’s Systems and Control Lab and lead researcher of ARNL, delivered a technical presentation at ONERA – The French Aerospace Lab in Toulouse, titled: “Future Perspectives of Active Flutter Suppression Technologies Based on Recent Flight Tests”. The presentation provided an overview of the experimental flight campaigns carried out as part of FLEXOP and FliPASED H2020 research projects, emphasizing the world-first active flutter suppression flight tests successfully executed by a consortium of leading European aerospace institutions: HUN-REN SZTAKI, TUM, DLR, and ONERA.